Classifying a specific portion of an anatomical structure is often a critical component of a surgical procedure. For example, treatment of a variety of neurological disorders involves implanting a neurostimulator, or the like, into the brain of a patient. This procedure, referred to as deep brain stimulation (DBS) is an effective surgical treatment for neurological disorders such as Parkinson's disease, for example. DBS involves surgically implanting a neurostimulator for electrically stimulating a target neural structure within the brain.
Current techniques for locating and classifying a target neural structure include a process known as microelectrode recording (MER). MER is performed during surgery, just prior to implantation of the neurostimulator. During MER, an electrode is inserted through a small opening in the skull and encounters several different neural structures before reaching the target neural structure. While traversing the brain toward the target neural structure, the electrode transduces neural activity into an acoustic signal. The acoustic signal is monitored to determine when the target neural structure has been reached.
A problem with this MER technique is that it is inexact and subject to variable interpretation. Different personnel listening to the audio signal can determine that the target structure has been reached at different times. Another problem is that specifically trained personnel are typically required to interpret the audio signal. Further, the technique is affected by uncontrollable factors in the operating room, such as the quality of the microelectrode, recording cables, and the audio equipment.